Biology subjects

Kim, M.

Publications and source records attributed to Kim, M..

351 records · Page 20Linked to original sources

bioRxiv2018

Compendium of Synovial Signatures Identifies Pathologic Characteristics for Predicting Treatment Response in Rheumatoid Arthritis

Treatment of patients with rheumatoid arthritis (RA) is challenging due to clinical heterogeneity and variability. Integration of RA synovial genome-scale transcriptomic profiling of different patient cohorts can provide insights on the causal basis of drug responses. A normalized compendium was built that consists of 256 RA synovial samples that cover an intersection of 11,769 genes from 11 datasets. Differentially expression genes (DEGs) that were identified in three independent methods were fed into functional network analysis, with subsequent grouping of the samples based on a non-negative matrix factorization method. Finally, we built a predictive model for treatment response by using RA-relevant pathway activation scores and four machine learning classification techniques. We identified 876 up-regulated DEGs including 24 known genetic risk factors and 8 drug targets. DEG-based subgrouping revealed 3 distinct RA patient clusters with distinct activity signatures for RA-relevant pathways. In the case of infliximab, we constructed a classifier of drug response that was highly accurate with an AUC/AUPR of 0.92/0.86. The most informative pathways in achieving this performance were the NF{kappa}B-, Fc{varepsilon}RI- TCR-, and TNF signaling pathways. Similarly, the expression of the HMMR, PRPF4B, EVI2A, RAB27A, MALT1, SNX6, and IFIH1 genes contributed in predicting the patient outcome. Construction and analysis of normalized synovial transcriptomic compendia can provide useful insights for understanding RA-related pathway involvement and drug responses for individual patients. The efficacy of a predictive model for personalized drug response has been demonstrated and can be generalized to several drugs, co-morbidities, and other relevant features.

bioinformatics↗

bioRxiv2018

YAP1 Oncogene is a Context-specific Driver for Pancreatic Ductal Adenocarcinoma

AbstractTranscriptomic profiling classifies pancreatic ductal adenocarcinoma (PDAC) into several molecular subtypes with distinctive histological and clinical characteristics. However, little is known about the molecular mechanisms that define each subtype and their correlation with clinical outcome. Mutant KRAS is the most prominent driver in PDAC, present in over 90% of tumors, but the dependence of tumors on oncogenic KRAS signaling varies between subtypes. In particular, squamous subtype are relatively independent of oncogenic KRAS signaling and typically display much more aggressive clinical behavior versus progenitor subtype. Here, we identified that YAP1 activation is enriched in the squamous subtype and associated with poor prognosis. Activation of YAP1 in progenitor subtype cancer cells profoundly enhanced malignant phenotypes and transformed progenitor subtype cells into squamous subtype. Conversely, depletion of YAP1 specifically suppressed tumorigenicity of squamous subtype PDAC cells. Mechanistically, we uncovered a significant positive correlation between WNT5A expression and the YAP1 activity in human PDAC, and demonstrated that WNT5A overexpression led to YAP1 activation and recapitulated YAP1-dependent but Kras-independent phenotype of tumor progression and maintenance. Thus, our study identifies YAP1 oncogene as a major driver of squamous subtype PDAC and uncovers the role of WNT5A in driving PDAC malignancy through activation of the YAP pathway.

cancer biology↗

bioRxiv2018

Multiplex Chromatin Interaction Analysis with Single-Molecule Precision

We describe a microfluidics-based strategy for genome-wide analysis of multiplex chromatin interactions with single-molecule precision. In multiplex chromatin interaction analysis (multi-ChIA), individual chromatin complexes are partitioned into droplets that contain a gel bead with unique DNA barcode, in which tethered chromatin DNA fragments are barcoded and amplified for sequencing and mapping to demarcate chromatin contacts. Thus, multi-ChIA has the unprecedented ability to uncover multiplex chromatin interactions at single-molecule level, which has been impossible using previous methods that rely on analyzing pairwise contacts via proximity ligation. We demonstrate that multiplex chromatin interactions predominantly contribute to topologically associated domains, and clusters of gene promoters and enhancers provide a fundamental topological framework for co-transcriptional regulation.

genomics↗

bioRxiv2017

Lamins organize the global three-dimensional genome from the nuclear periphery

Lamins are structural components of the nuclear lamina (NL) that regulate genome organization and gene expression, but the mechanism remains unclear. Using Hi-C, we show that lamins maintain proper interactions among the topologically associated chromatin domains (TADs) but not their overall architecture. Combining Hi-C with fluorescence in situ hybridization (FISH) and analyses of lamina-associated domains (LADs), we reveal that lamin loss causes expansion or detachment of specific LADs in mouse ES cells. The detached LADs disrupt 3D interactions of both LADs and interior chromatin. 4C and epigenome analyses further demonstrate that lamins maintain the active and repressive chromatin domains among different TADs. By combining these studies with transcriptome analyses, we found a significant correlation between transcription changes and the changes of active and inactive chromatin domain interactions. These findings provide a foundation to further study how the nuclear periphery impacts genome organization and transcription in development and NL-associated diseases.\n\nHighlightsO_LILamin loss does not affect the overall TAD structure but alters TAD-TAD interactions\nC_LIO_LILamin null ES cells exhibit decondensation or detachment of specific LAD regions\nC_LIO_LIExpansion and detachment of LADs can alter genome-wide 3D chromatin interactions\nC_LIO_LIAltered chromatin domain interactions are correlated with altered transcription\nC_LI

genomics↗

bioRxiv2017

Confronting the elephant in the room - verbal paired associates and the hippocampus

It is widely agreed that patients with bilateral hippocampal damage are impaired at binding pairs of words together. Consequently, the verbal paired associates (VPA) task has become emblematic of hippocampal function. This VPA deficit is not well understood, and is particularly difficult for hippocampal theories with a visuospatial bias to explain (e.g., cognitive map and scene construction theories). Resolving the tension among hippocampal theories concerning the VPA could be important for leveraging a fuller understanding of hippocampal function. Notably, VPA tasks typically use high imagery concrete words and so conflate imagery and binding. To determine why VPA engages the hippocampus, we devised an fMRI encoding task involving closely matched pairs of scene words, pairs of object words and pairs of very low imagery abstract words. We found that the anterior hippocampus was engaged during processing of both scene and object word pairs in comparison to abstract word pairs, despite binding occurring in all conditions. This was also the case when just subsequently remembered stimuli were considered. Moreover, for object word pairs, fMRI activity patterns in anterior hippocampus were more similar to those for scene imagery than object imagery. This was especially evident in participants who were high imagery users, and not in mid and low imagery users. Overall, our results show that hippocampal engagement during VPA, even when object word pairs are involved, seems to be evoked by scene imagery rather than binding. This may help to resolve the issue that visuospatial hippocampal theories have in accounting for verbal memory.

neuroscience↗

bioRxiv2017

Hippocampus, retrosplenial and parahippocampal cortices encode multi-compartment 3D space in a hierarchical manner

Humans commonly operate within 3D environments such as multi-floor buildings and yet there is a surprising dearth of studies that have examined how these spaces are represented in the brain. Here we had participants learn the locations of paintings within a virtual multi-level gallery building and then used behavioural tests and fMRI repetition suppression analyses to investigate how this 3D multi-compartment space was represented, and whether there was a bias in encoding vertical and horizontal information. We found faster response times for within-room egocentric spatial judgments and behavioural priming effects of visiting the same room, providing evidence for a compartmentalised representation of space. At the neural level, we observed a hierarchical encoding of 3D spatial information, with left anterior hippocampus representing local information within a room, while retrosplenial cortex, parahippocampal cortex and posterior hippocampus represented room information within the wider building. Of note, both our behavioural and neural findings showed that vertical and horizontal location information was similarly encoded, suggesting an isotropic representation of 3D space even in the context of a multi-compartment environment. These findings provide much-needed information about how the human brain supports spatial memory and navigation in buildings with numerous levels and rooms.

neuroscience↗

bioRxiv2017

ChIPWig: A Random Access-Enabling Lossless And Lossy Compression Method For ChIP-Seq Data

MotivationThe past decade has witnessed a rapid development of data acquisition technologies that enable integrative genomic and proteomic analysis. One such technology is chromatin immunoprecipitation sequencing (ChIP-seq), developed for analyzing interactions between proteins and DNA via next-generation sequencing technologies. As ChIP-seq experiments are inexpensive and time-efficient, massive datasets from this domain have been acquired, introducing significant storage and maintenance challenges. To address the resulting Big Data problems, we propose a state-of-the-art lossless and lossy compression framework specifically designed for ChIP-seq Wig data, termed ChIPWig. Wig is a standard file format, which in this setting contains relevant read density information crucial for visualization and downstream processing. ChIPWig may be executed in two different modes: lossless and lossy. Lossless ChIPWig compression allows for random access and fast queries in the file through careful variable-length block-wise encoding. ChIPWig also stores the summary statistics of each block needed for guided access. Lossy ChIPWig, in contrast, performs quantization of the read density values before feeding them into the lossless ChIPWig compressor. Nonuniform lossy quantization leads to further reductions in the file size, while maintaining the same accuracy of the ChIP-seq peak calling and motif discovery pipeline based on the NarrowPeaks method tailor-made for Wig files. The compressors are designed using new statistical modeling approaches coupled with delta and arithmetic encoding.\n\nResultsWe tested the ChIPWig compressor on a number of ChIP-seq datasets generated by the ENCODE project. Lossless ChIPWig reduces the file sizes to merely 6% of the original, and offers an average 6-fold compression rate improvement compared to bigWig. The running times for compression and decompression are comparable to those of bigWig. The compression and decompression speed rates are of the order of 0.2 MB/sec using general purpose computers. ChIPWig with random access only slightly degrades the performance and running time when compared to the standard mode. In the lossy mode, the average file sizes reduce by 2-fold compared to the lossless mode. Most importantly, near-optimal nonuniform quantization with respect to mean-square distortion does not affect peak calling and motif discovery results on the data tested.\n\nAvailability and ImplementationSource code and binaries freely available for download at https://github.com/vidarmehr/ChIPWig\n\nContactmilenkov@illinois.edu\n\nSupplementary informationIs available on bioRxiv.

bioinformatics↗

bioRxiv2017

TeachEnG: a Teaching Engine for Genomics

MotivationBioinformatics is a rapidly growing field that has emerged from the synergy of computer science, statistics, and biology. Given the interdisciplinary nature of bioinformatics, many students from diverse fields struggle with grasping bioinformatic concepts only from classroom lectures. Interactive tools for helping students reinforce their learning would be thus desirable. Here, we present an interactive online educational tool called TeachEnG (acronym for Teaching Engine for Genomics) for reinforcing key concepts in sequence alignment and phylogenetic tree reconstruction. Our instructional games allow students to align sequences by hand, fill out the dynamic programming matrix in the Needleman-Wunsch global sequence alignment algorithm, and reconstruct phylogenetic trees via the maximum parsimony and Unweighted Pair Group Method with Arithmetic mean (UPGMA) algorithms. With an easily accessible interface and instant visual feedback, TeachEnG will help promote active learning in bioinformatics.\n\nAvailability and Implementation: TeachEnG is freely available at http://song.igb.illinois.edu/TeachEnG/. It is written in JavaScript and compatible with Firefox, Safari, Chrome, and Microsoft Edge.\n\nContact: songi@illinois.edu

bioinformatics↗

bioRxiv2017

Fine-scale human population structure in southern Africa reflects ecogeographic boundaries

Recent genetic studies have established that the KhoeSan populations of southern Africa are distinct from all other African populations and have remained largely isolated during human prehistory until about 2,000 years ago. Dozens of different KhoeSan groups exist, belonging to three different language families, but very little is known about their population history. We examine new genome-wide polymorphism data and whole mitochondrial genomes for more than one hundred South Africans from the =Khomani San and Nama populations of the Northern Cape, analyzed in conjunction with 19 additional southern African populations. Our analyses reveal fine-scale population structure in and around the Kalahari Desert. Surprisingly, this structure does not always correspond to linguistic or subsistence categories as previously suggested, but rather reflects the role of geographic barriers and the ecology of the greater Kalahari Basin. Regardless of subsistence strategy, the indigenous Khoe-speaking Nama pastoralists and the N|u-speaking =Khomani (formerly hunter-gatherers) share ancestry with other Khoe-speaking forager populations that form a rim around the Kalahari Desert. We reconstruct earlier migration patterns and estimate that the southern Kalahari populations were among the last to experience gene flow from Bantu-speakers, approximately 14 generations ago. We conclude that local adoption of pastoralism, at least by the Nama, appears to have been primarily a cultural process with limited genetic impact from eastern Africa.\n\nData depositionData files are freely available on the Henn Lab website: http://ecoevo.stonybrook.edu/hennlab/data-software/\n\nSummaryDistinct, spatially organized ancestries demonstrate fine-scale population structure in southern Africa, implying a more complex history of the KhoeSan than previously thought. Southern KhoeSan ancestry in the Nama and =Khomani is shared in a rim around the Kalahari Desert. We hypothesize that there was recent migration of pastoralists from East Africa into southern Africa, independent of the Bantu-expansion, but the spread of pastoralism within southern Africa occurred largely by cultural diffusion.

genetics↗